Implicit Sentiment Mining in Twitter Streams

For our November Meetup, we're very happy to have Maksim (Max) Tsvetovat from local analytics consulting firm Deepmile Networks (http://www.deepmile.com/), talking about extracting sentiment from Twitter data. Although the idea of using billions of tweets to learn about opinions is appealing, getting it to work in a compelling and valuable manner has been fraught with difficulty. Max will bring us up to speed, and discuss a method that works well for certain domains.

Notes: We're back at Google for this event! And we'll be continuing our experiment with informal pre-event themed networking -- please come early to meet and chat with people interested in Natural Language Processing!

Agenda:

6:30pm -- Networking and Refreshments (Discussion theme: NLP) 7:00pm -- Introduction 7:15pm -- Max's presentation and Q&A 8:30pm -- Post presentation conversations 8:45pm -- Adjourn for Data Drinks (location TBA) Abstract:

In this talk, I will describe a new method for estimating sentiment in online speech. This method does not rely on pre-defined lists of "good" or "bad" words -- but, rather, measures affinity toward a subject, brand, politician, etc. by locating and measuring psycholinguistic similarities between speakers and producing aggregate sentiment statistics. This method is ideally suited to understanding sentiment toward politicians, journalists, advertisers -- anyone that produces large amounts of direct speech. While this limits the domains in which this method is applicable, its accuracy
increases significantly.

Bio:

Max is the Chief Technology Officer at DeepMile (http://www.deepmile.com/). He has a PhD from Carnegie Mellon University and is currently a Research Assistant Professor at George Mason University (http://www.css.gmu.edu/node/8?q=node/22) where he teaches Social Network Analysis. He is widely published in computer science, organizational theory and social network journals, and is a regular presenter at industry conferences. To learn more about Max and his research, you can explore his website -- http://www.tsvetovat.org . You should also buy his book, Social Network Analysis for Startups (http://shop.oreilly.com/product/0636920020424.do).